What is Gyazo Mcp Server

gyazo-mcp-server is a Model Context Protocol server designed for integrating Gyazo images, allowing AI assistants to access and interact with Gyazo images through the Model Context Protocol.

Use cases

Use cases include retrieving the latest images for display in applications, integrating image metadata for enhanced user experiences, and utilizing OCR data for text extraction from images.

How to use

To use gyazo-mcp-server, install the necessary dependencies, set up your Gyazo account and API access token, and configure the server in your application. You can run it directly or via Docker.

Key features

Key features include access to Gyazo images via URIs, metadata retrieval, support for various image formats, and tools for fetching the latest images and their associated OCR data.

Where to use

gyazo-mcp-server can be used in applications that require image integration, such as AI assistants, content management systems, and any platform that utilizes Gyazo for image storage.

gyazo-mcp-server

A Model Context Protocol server for Gyazo image integration

This is a TypeScript-based MCP server that provides access to Gyazo images. It allows AI assistants to access and interact with Gyazo images through the Model Context Protocol, providing:

• Resources representing Gyazo images with URIs and metadata
• Tools for searching, fetching, and uploading images
• Image content and metadata access via the Gyazo API

Features

Resources

• List and access Gyazo images via gyazo-mcp:// URIs
• Each image includes:
  • Original image content
  • Metadata (title, description, app, URL)
  • OCR data (if available)
• Supports various image formats (JPEG, PNG, etc.)

Tools

• gyazo_search - Full-text search for captures uploaded by users on Gyazo

  • Search by keyword, title, app, URL, or date range
  • Supports pagination for browsing multiple results
  • Returns matching image URIs and metadata

• gyazo_image - Fetch image content and metadata from Gyazo

  • Retrieve specific images by ID or URL
  • Returns both image content and detailed metadata

• gyazo_latest_image - Fetch the most recent image from Gyazo

  • Returns both image content and metadata
  • Includes OCR text if available

• gyazo_upload - Upload an image to Gyazo

  • Upload images with base64 encoded image data
  • Add optional metadata like title, description, referer URL, and app name
  • Returns the uploaded image’s permalink URL and ID

Installation

NPM Package

The easiest way to install the Gyazo MCP server is via npm:

npm install -g @notainc/gyazo-mcp-server

Prerequisites

• Create a Gyazo account if you don’t have one: https://gyazo.com
• Get your Gyazo API access token from: https://gyazo.com/api
  • Click “Register applications” button
  • Click “New Application” button
  • Fill in the form with your app name and description
    • Name and Callback URL are required
    • You can use http://localhost for the Callback URL
  • Click “Submit” button
  • Click application name to view details
  • Scroll down to “Your Access Token”
  • Click “Generate” button
  • Copy “Your access token” value
• Set the GYAZO_ACCESS_TOKEN environment variable with your token

Claude Desktop Integration

To use with Claude Desktop, add the server config:

On MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json

Using NPM package (recommended)

{
  "mcpServers": {
    "gyazo-mcp-server": {
      "command": "npx",
      "args": [
        "@notainc/gyazo-mcp-server"
      ],
      "env": {
        "GYAZO_ACCESS_TOKEN": "your-access-token-here"
      }
    }
  }
}

Using Docker (optional)

{
  "mcpServers": {
    "gyazo-mcp-server": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "GYAZO_ACCESS_TOKEN",
        "gyazo-mcp-server"
      ],
      "env": {
        "GYAZO_ACCESS_TOKEN": "your-access-token-here"
      }
    }
  }
}

Development

Install dependencies:

npm ci

Build the server:

npm run build

For development with auto-rebuild:

npm run watch

Docker Build (optional)

npm run image:build